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Population-based blood screening for preclinical Alzheimer's disease in a British birth cohort at age 70.
Keshavan, Ashvini; Pannee, Josef; Karikari, Thomas K; Rodriguez, Juan Lantero; Ashton, Nicholas J; Nicholas, Jennifer M; Cash, David M; Coath, William; Lane, Christopher A; Parker, Thomas D; Lu, Kirsty; Buchanan, Sarah M; Keuss, Sarah E; James, Sarah-Naomi; Murray-Smith, Heidi; Wong, Andrew; Barnes, Anna; Dickson, John C; Heslegrave, Amanda; Portelius, Erik; Richards, Marcus; Fox, Nick C; Zetterberg, Henrik; Blennow, Kaj; Schott, Jonathan M.
Afiliação
  • Keshavan A; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Pannee J; Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden.
  • Karikari TK; Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden.
  • Rodriguez JL; Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden.
  • Ashton NJ; Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden.
  • Nicholas JM; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
  • Cash DM; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Coath W; National Institute for Health Research Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation Trust, London, UK.
  • Lane CA; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Parker TD; Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK.
  • Lu K; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Buchanan SM; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Keuss SE; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • James SN; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Murray-Smith H; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Wong A; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Barnes A; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Dickson JC; MRC Unit for Lifelong Health and Ageing at UCL, London, UK.
  • Heslegrave A; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
  • Portelius E; MRC Unit for Lifelong Health and Ageing at UCL, London, UK.
  • Richards M; Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK.
  • Fox NC; Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK.
  • Zetterberg H; UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, UK.
  • Blennow K; Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden.
  • Schott JM; MRC Unit for Lifelong Health and Ageing at UCL, London, UK.
Brain ; 144(2): 434-449, 2021 03 03.
Article em En | MEDLINE | ID: mdl-33479777
ABSTRACT
Alzheimer's disease has a preclinical stage when cerebral amyloid-ß deposition occurs before symptoms emerge, and when amyloid-ß-targeted therapies may have maximum benefits. Existing amyloid-ß status measurement techniques, including amyloid PET and CSF testing, are difficult to deploy at scale, so blood biomarkers are increasingly considered for screening. We compared three different blood-based techniques-liquid chromatography-mass spectrometry measures of plasma amyloid-ß, and single molecule array (Simoa) measures of plasma amyloid-ß and phospho-tau181-to detect cortical 18F-florbetapir amyloid PET positivity (defined as a standardized uptake value ratio of >0.61 between a predefined cortical region of interest and eroded subcortical white matter) in dementia-free members of Insight 46, a substudy of the population-based British 1946 birth cohort. We used logistic regression models with blood biomarkers as predictors of amyloid PET status, with or without age, sex and APOE ε4 carrier status as covariates. We generated receiver operating characteristics curves and quantified areas under the curves to compare the concordance of the different blood tests with amyloid PET. We determined blood test cut-off points using Youden's index, then estimated numbers needed to screen to obtain 100 amyloid PET-positive individuals. Of the 502 individuals assessed, 441 dementia-free individuals with complete data were included; 82 (18.6%) were amyloid PET-positive. The area under the curve for amyloid PET status using a base model comprising age, sex and APOE ε4 carrier status was 0.695 (95% confidence interval 0.628-0.762). The two best-performing Simoa plasma biomarkers were amyloid-ß42/40 (0.620; 0.548-0.691) and phospho-tau181 (0.707; 0.646-0.768), but neither outperformed the base model. Mass spectrometry plasma measures performed significantly better than any other measure (amyloid-ß1-42/1-40 0.817; 0.770-0.864 and amyloid-ß composite 0.820; 0.775-0.866). At a cut-off point of 0.095, mass spectrometry measures of amyloid-ß1-42/1-40 detected amyloid PET positivity with 86.6% sensitivity and 71.9% specificity. Without screening, to obtain 100 PET-positive individuals from a population with similar amyloid PET positivity prevalence to Insight 46, 543 PET scans would need to be performed. Screening using age, sex and APOE ε4 status would require 940 individuals, of whom 266 would proceed to scan. Using mass spectrometry amyloid-ß1-42/1-40 alone would reduce these numbers to 623 individuals and 243 individuals, respectively. Across a theoretical range of amyloid PET positivity prevalence of 10-50%, mass spectrometry measures of amyloid-ß1-42/1-40 would consistently reduce the numbers proceeding to scans, with greater cost savings demonstrated at lower prevalence.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Fragmentos de Peptídeos / Peptídeos beta-Amiloides / Doença de Alzheimer Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Aged / Female / Humans / Male Idioma: En Revista: Brain Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Fragmentos de Peptídeos / Peptídeos beta-Amiloides / Doença de Alzheimer Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Aged / Female / Humans / Male Idioma: En Revista: Brain Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido